Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy
Abstract Based on a selection of 101 articles published from 2013 to 2022, this study systematically reviews the application of intelligent techniques and optimization algorithms in textile colour management. Specifically, the study explores how these techniques have been applied to four subfields w...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-03-01
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| Series: | Fashion and Textiles |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40691-024-00375-x |
| _version_ | 1827321561439272960 |
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| author | Senbiao Liu Yaohui Keane Liu Kwan-yu Chris Lo Chi-wai Kan |
| author_facet | Senbiao Liu Yaohui Keane Liu Kwan-yu Chris Lo Chi-wai Kan |
| author_sort | Senbiao Liu |
| collection | DOAJ |
| description | Abstract Based on a selection of 101 articles published from 2013 to 2022, this study systematically reviews the application of intelligent techniques and optimization algorithms in textile colour management. Specifically, the study explores how these techniques have been applied to four subfields within textile colour management: colour matching and prediction, colour difference detection and assessment, colour recognition and segmentation, and dye solution concentration and decolourization. Following an introduction to intelligent techniques and optimization algorithms in textile colour management, the study describes the specific applications of these techniques in the field over the past decade. Descriptive statistics are used to analyse trends in the use of these techniques and optimization algorithms, and comparative performances indicate the effectiveness of the techniques and algorithms. The study finds that the primary intelligent techniques used in the field of textile colour management include artificial neural networks (ANN), support vector machines (SVM) such as SVM, LSSVM, LSSVR, SLSSVR, FWSVR, fuzzy logic (FL) and adaptive neuro-fuzzy inference systems (ANFIS), clustering algorithms (e.g., K-means, FCM, X-means algorithms), and extreme learning machines (ELM) such as ELM, OSLEM, KELM, RELM. The main optimization algorithms used include response surface methodology (RSM), genetic algorithms (GA), particle swarm optimization (PSO), and differential evolution (DE). Finally, the study proposes a comparison of the performance of intelligent techniques and optimization algorithms, summarizes the relevant research trends, and suggests future research opportunities and directions, besides stating the limitations of this paper. |
| first_indexed | 2024-04-25T01:08:17Z |
| format | Article |
| id | doaj.art-8326a54b731e4cb6a0c3288be86b3f92 |
| institution | Directory Open Access Journal |
| issn | 2198-0802 |
| language | English |
| last_indexed | 2024-04-25T01:08:17Z |
| publishDate | 2024-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Fashion and Textiles |
| spelling | doaj.art-8326a54b731e4cb6a0c3288be86b3f922024-03-10T12:06:14ZengSpringerOpenFashion and Textiles2198-08022024-03-0111113810.1186/s40691-024-00375-xIntelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracySenbiao Liu0Yaohui Keane Liu1Kwan-yu Chris Lo2Chi-wai Kan3School of Fashion and Textiles, The Hong Kong Polytechnic UniversityDepartment of Construction Technology and Engineering, Technological and Higher Education Institute of Hong KongSchool of Fashion and Textiles, The Hong Kong Polytechnic UniversitySchool of Fashion and Textiles, The Hong Kong Polytechnic UniversityAbstract Based on a selection of 101 articles published from 2013 to 2022, this study systematically reviews the application of intelligent techniques and optimization algorithms in textile colour management. Specifically, the study explores how these techniques have been applied to four subfields within textile colour management: colour matching and prediction, colour difference detection and assessment, colour recognition and segmentation, and dye solution concentration and decolourization. Following an introduction to intelligent techniques and optimization algorithms in textile colour management, the study describes the specific applications of these techniques in the field over the past decade. Descriptive statistics are used to analyse trends in the use of these techniques and optimization algorithms, and comparative performances indicate the effectiveness of the techniques and algorithms. The study finds that the primary intelligent techniques used in the field of textile colour management include artificial neural networks (ANN), support vector machines (SVM) such as SVM, LSSVM, LSSVR, SLSSVR, FWSVR, fuzzy logic (FL) and adaptive neuro-fuzzy inference systems (ANFIS), clustering algorithms (e.g., K-means, FCM, X-means algorithms), and extreme learning machines (ELM) such as ELM, OSLEM, KELM, RELM. The main optimization algorithms used include response surface methodology (RSM), genetic algorithms (GA), particle swarm optimization (PSO), and differential evolution (DE). Finally, the study proposes a comparison of the performance of intelligent techniques and optimization algorithms, summarizes the relevant research trends, and suggests future research opportunities and directions, besides stating the limitations of this paper.https://doi.org/10.1186/s40691-024-00375-xIntelligent techniquesOptimisation algorithmsTextile colour managementPerformance comparison referenceReview |
| spellingShingle | Senbiao Liu Yaohui Keane Liu Kwan-yu Chris Lo Chi-wai Kan Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy Fashion and Textiles Intelligent techniques Optimisation algorithms Textile colour management Performance comparison reference Review |
| title | Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy |
| title_full | Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy |
| title_fullStr | Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy |
| title_full_unstemmed | Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy |
| title_short | Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy |
| title_sort | intelligent techniques and optimization algorithms in textile colour management a systematic review of applications and prediction accuracy |
| topic | Intelligent techniques Optimisation algorithms Textile colour management Performance comparison reference Review |
| url | https://doi.org/10.1186/s40691-024-00375-x |
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